scholarly journals Boundary conditions for the Middle Miocene Climate Transition (MMCT v1.0)

2017 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz

Abstract. The Middle Miocene Climate Transition was characterized by major Antarctic ice-sheet expansion and global cooling during the interval ~ 15–13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry and vegetation. Additionally, Antarctic ice volume and geometry, sea-level and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.

2018 ◽  
Vol 11 (4) ◽  
pp. 1607-1626 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz

Abstract. The Middle Miocene Climate Transition was characterized by major Antarctic ice sheet expansion and global cooling during the interval ∼ 15–13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry, and vegetation. Additionally, Antarctic ice volume and geometry, sea level, and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The MMCO and MMG boundary conditions have been successfully applied to the Community Climate System Model version 3 (CCSM3) to provide evidence of their suitability for global climate modeling. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.


2018 ◽  
Vol 31 (22) ◽  
pp. 9151-9173 ◽  
Author(s):  
Richard Davy

Here, we present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change.


2018 ◽  
Vol 11 (1) ◽  
pp. 200-216 ◽  
Author(s):  
Reza Haji Hosseini ◽  
Saeed Golian ◽  
Jafar Yazdi

Abstract Assessment of climate change in future periods is considered necessary, especially with regard to probable changes to water resources. One of the methods for estimating climate change is the use of the simulation outputs of general circulation models (GCMs). However, due to the low resolution of these models, they are not applicable to regional and local studies and downscaling methods should be applied. The purpose of the present study was to use GCM models' outputs for downscaling precipitation measurements at Amameh station in Latyan dam basin. For this purpose, the observation data from the Amameh station during the 1980–2005 period, 26 output variables from two GCM models, namely, HadCM3 and CanESM2 were used. Downscaling was performed by three data-driven methods, namely, artificial neural network (ANN), nonparametric K-nearest neighborhood (KNN) method, and adaptive network-based fuzzy inference system method (ANFIS). Comparison of the monthly results showed the superiority of KNN compared to the other two methods in simulating precipitation. However, all three, ANN, KNN, and ANFIS methods, showed satisfactory results for both HadDCM3 and CanESM2 GCM models in downscaling precipitation in the study area.


2010 ◽  
Vol 49 (10) ◽  
pp. 2147-2158 ◽  
Author(s):  
Peter Caldwell

Abstract In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California and compared. Several averaging methodologies are considered and all are found to give similar values when the model grid spacing is less than 3°. This suggests that California is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict California precipitation. This appears to be due mainly to the overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge–satellite observations, which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait that does not seem to be tied to model resolution. The GCM daily and interannual variabilities are generally underpredicted.


2014 ◽  
Vol 6 (2) ◽  
pp. 288-299 ◽  
Author(s):  
K. Srinivasa Raju ◽  
D. Nagesh Kumar

Eleven general circulation models/global climate models (GCMs) – BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1 – are evaluated for Indian climate conditions using the performance indicator, skill score (SS). Two climate variables, temperature T (at three levels, i.e. 500, 700, 850 mb) and precipitation rate (Pr) are considered resulting in four SS-based evaluation criteria (T500, T700, T850, Pr). The multicriterion decision-making method, technique for order preference by similarity to an ideal solution, is applied to rank 11 GCMs. Efforts are made to rank GCMs for the Upper Malaprabha catchment and two river basins, namely, Krishna and Mahanadi (covered by 17 and 15 grids of size 2.5° × 2.5°, respectively). Similar efforts are also made for India (covered by 73 grid points of size 2.5° × 2.5°) for which an ensemble of GFDL2.0, INGV-ECHAM4, UKMO-HADCM3, MIROC3, BCCR-BCCM2.0 and GFDL2.1 is found to be suitable. It is concluded that the proposed methodology can be applied to similar situations with ease.


Author(s):  
Syed Rouhullah Ali ◽  
Junaid N. Khan ◽  
Yogesh Pandey ◽  
Mehraj U. Din Dar ◽  
Mudasir Shafi ◽  
...  

Global atmospheric general circulation models (GCMs) were developed to simulate the current climate and are used to predict climate change. Several Global Climate Models (GCM’s) are available for understanding and projecting climate change. GCM requires to be downscale on a basin-scale and combined with applicable hydrological models considering all components of the hydrologic process. The performance of such coupling models, such as groundwater recharge quantification, should help to make correct adaptation strategies. Climate change has the ability to affect both the quality and quantity of available groundwater, mainly through impact on recharge, evapotranspiration, pump-age and abstraction. As a consequence, groundwater is a significant contributor to the streamflow in areas with fairly shallow water resources, knowing how climate change could impact groundwater supplies is crucial for long-term water resource management. The effect of climate change on groundwater systems is very difficult to predict. Part of the uncertainty of climate predictions is embedded of possibilities. Better insights, a more profound knowledge of mechanisms and modeling skills are required to determine this critical resource’s potential in the face of predicted climate change.


2020 ◽  
Author(s):  
Jadwiga Richter ◽  
Francois Lott ◽  

<p>We compare the response of the quasi-biennial oscillation (QBO) to a warming climate in eleven atmosphere general circulation models that performed time-slice simulations for present-day, doubled,  and  quadrupled CO<sub>2</sub> climates.  No consistency was found among the models for the QBO period response, with the period decreasing by eight months in some models and lengthening by up to thirteen months in others in the doubled CO<sub>2</sub>  simulations.  In the quadruped CO<sub>2</sub> simulations  a reduction in QBO period of 14 months was found in some models, whereas in several others the tropical oscillation no longer resembled the present day QBO, although could still be identified in the deseasonalized zonal mean zonal wind timeseries.  In contrast, all the models projected a decrease in the  QBO amplitude in a warmer climate with the largest relative decrease  near 60 hPa. In simulations with doubled and quadrupled CO<sub>2</sub> the multi-model mean QBO amplitudes decreased by 36\% and 51\%, respectively. Across the  models the differences in the QBO period response were most strongly related to how the gravity wave momentum flux entering the stratosphere and tropical vertical residual velocity responded to the increases in CO<sub>2</sub> amounts. Likewise it was found that the robust decrease in QBO amplitudes was correlated across the models to changes in vertical residual velocity, parameterized gravity wave momentum fluxes, and to some degree the resolved upward wave flux.  We argue that uncertainty in the representation of the parameterized gravity waves is the most likely cause of the spread among the eleven models in the QBO's response to climate change.</p>


2020 ◽  
Author(s):  
Matthias Scheiter ◽  
Marius Schaefer ◽  
Eduardo Flández ◽  
Deniz Bozkurt ◽  
Ralf Greve

Abstract. Glaciers and ice caps are thinning and retreating along the entire Andes ridge, and drivers of this mass loss vary between the different climate zones. The southern part of the Andes (Wet Andes) has the highest abundance of glaciers in number and size, and a proper understanding of ice dynamics is important to assess their evolution. In this contribution, we apply the ice sheet model SICOPOLIS to the Mocho-Choshuenco ice cap in the Chilean Lake District (40° S, 72° W, Wet Andes) to reproduce its current state and to project its evolution until the end of the 21st century under different global warming scenarios. First, we create a model spin-up using surface mass balance data observed on the south-eastern catchment, extrapolating them to the whole ice cap using an exposition-dependent parameterization. This spin-up is able to reproduce the most important present-day glacier features. Based on the spin-up, we then run the model 80 years into the future, forced by projected surface temperature anomalies from different global circulation models under different radiative pathway scenarios to obtain estimates of the ice cap's state by the end of the 21st century. The mean projected ice volume losses are 25 ± 19 % (RCP2.6), 64 ± 14 % (RCP4.5) and 94 ± 3 % (RCP8.5) with respect to the ice volume estimated by radio-echo sounding data from 2013. We estimate the uncertainty of our projections based on the spread of the results when forcing with different global climate models and on the uncertainty associated with the variation of the equilibrium line altitude with temperature change. Considering our results, we project an considerable deglaciation of the Chilean Lake District by the end of the 21st century.


2016 ◽  
Vol 29 (24) ◽  
pp. 8823-8840 ◽  
Author(s):  
Paolo Davini ◽  
Fabio D’Andrea

Abstract The correct simulation of midlatitude atmospheric blocking has always been a main concern since the earliest days of numerical modeling of Earth’s atmosphere. To this day blocking represents a considerable source of error for general circulation models from both a numerical weather prediction and a climate perspective. In the present work, 20 years of global climate model (GCM) developments are analyzed from the special point of view of Northern Hemisphere atmospheric blocking simulation. Making use of a series of equivalent metrics, three generations of GCMs are compared. This encompasses a total of 95 climate models, many of which are different—successive—versions of the same model. Results from model intercomparison projects AMIP1 (1992), CMIP3 (2007), and CMIP5 (2012) are taken into consideration. Although large improvements are seen over the Pacific Ocean, only minor advancements have been achieved over the Euro-Atlantic sector. Some of the most recent GCMs still exhibit the same negative bias as 20 years ago in this region, associated with large geopotential height systematic errors. Some individual models, nevertheless, have improved and do show good performances in both sectors. Negligible differences emerge among ocean-coupled or atmosphere-only simulations, suggesting weak relevance of sea surface temperature biases. Conversely, increased horizontal resolution seems to be able to alleviate the Euro-Atlantic blocking bias.


1997 ◽  
Vol 25 ◽  
pp. 400-406 ◽  
Author(s):  
Martin Beniston ◽  
Wilfried Haeberli ◽  
Martin Hoelzle ◽  
Alan Taylor

While the capability of global and regional climate models in reproducing current climate has significantly improved over the past few years, the confidence in model results for remote regions, or those where complex orography is a dominant feature, is still relatively low. This is, in part, linked to the lack of observational data for model verification and intercomparison purposes.Glacier and permafrost observations are directly related to past and present energy flux patterns at the Earth-atmosphere interface and could be used as a proxy for air temperature and precipitation, particularly of value in remote mountain regions and boreal and Arctic zones where instrumental climate records are sparse or non-existent. It is particularly important to verify climate-model performance in these regions, as this is where most general circulation models (GCMs) predict the greatest changes in air temperatures in a warmer global climate.Existing datasets from glacier and permafrost monitoring sites in remote and high altitudes are described in this paper; the data could be used in model-verification studies, as a means to improving model performance in these regions.


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